Tag: Contact Centers

Beyond the Buzz: Is Your Contact Center Data Truly Gen AI-Ready with the Right Data Strategy? | Blog

In today’s fast-evolving customer experience (CX) landscape, data is often referred to as the “new oil”—a critical resource powering innovation and efficiency.  

Nowhere is this truer than in contact centers, where data from customer interactions fuels everything from service delivery to strategic decision-making. With generative AI (gen AI) entering the scene, this data is not just an asset but a requirement. For contact centers, data is the lifeblood that enables artificial intelligence (AI) to deliver real-time, personalized experiences, optimize workflows, and streamline issue resolutions. 

But before you jump into implementing gen AI, there’s a key question to address: Is your data ready?

The success of AI initiatives hinges not just on the quantity of data but its quality, accessibility, and structure. Data readiness becomes the foundation for any successful AI deployment, ensuring that your contact center is prepared to harness AI’s full potential. But what exactly is data readiness, and how can you assess whether your contact center has it? Let’s dive deeper…

Reach out to discuss this topic in depth. 

What is data readiness?

Data readiness is the state of your organization’s data in terms of quality, quantity, structure, and availability to support AI-driven solutions. In the context of gen AI in contact centers, it refers to having the right kind of structured and unstructured data—voice transcripts, chat logs and customer relationship management (CRM) interactions, etc.—that AI systems can process, learn from, and use to generate intelligent insights or automate workflows.

Think of it like cooking a gourmet meal: You can have the best kitchen equipment (AI tools), but if your ingredients (data) are spoiled or mismanaged, the final dish will be a disaster. The same goes for AI implementation in contact centers — without properly prepared data, even the most advanced gen AI tools can underperform.

What should your data be like for gen AI success?

For gen AI to work effectively in contact centers, the data needs to meet several key criteria:

Screenshot 2024 11 14 115134

Exhibit 1: Checklist for data readiness 

Source: Everest Group

Stages of data readiness

Understanding where your organization stands in its data readiness journey is key to planning for gen AI. Here are typical stages:

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Exhibit 2: Stages of Data Readiness 

Source: Everest Group

To identify your state in data readiness, answering the following questions will give you a clear picture of your current state:

Screenshot 2024 11 08 110144 1

Exhibit 3: Questions to identify your current state in data readiness 

Source: Everest Group

Tangible steps to improve data readiness

Once you identify your stage, you can follow the below approach to progress toward AI readiness:

Screenshot 2024 11 14 114922

Exhibit 4: Tangible steps to improve data readiness 

Source: Everest Group

Leveraging technology, automation, and AI to boost data readiness

Automation tools and AI can play a big role in speeding up the data readiness process. For instance:

  • Automation for data cleaning: Deploy Robotic Process Automation (RPA) for cleaning and structuring large datasets, eliminating repetitive manual tasks
  • AI-based feedback loops: Implement AI to constantly monitor data quality, identifying gaps and correcting inconsistencies in real-time
  • Self-learning systems: As your gen AI models evolve, create a feedback mechanism where the AI itself learns from the data it processes, ensuring continuous improvements

Conclusion

Data readiness isn’t a destination—it’s a continuous journey that ensures your contact center is prepared to maximize the potential of gen AI.

Whether you’re in the early stages of organizing your data or already utilizing advanced AI systems, taking steps to improve your data’s quality, accessibility, and contextual richness will dramatically impact your AI’s effectiveness.

As gen AI continues to evolve, ensuring your data is prepared will not only enhance the customer experience, but also drive efficiency and innovation across your contact center operations. Don’t let poor data hold your AI back—start optimizing today!

If you found this blog interesting, check out our blog focusing on Generative AI In Healthcare – A Game Changer Or Another Fad? | Blog – Everest Group (everestgrp.com), which delves deeper into another topic regarding gen AI. 

If you have questions or want to discuss CX strategies and solutions, please contact Mohit Kumar or Chhandak Biswas. 

Which Call Center Agent Model Is Right for Your Business during and after COVID-19? | Blog

Today, most companies have staff working from home due to the pandemic. Although customer experience management (CXM) agents aren’t essential workers in the truest sense, consumers sheltering in the safety of their homes for months on end have relied on them so heavily for wide-ranging reasons that they might as well have considered them so. What those consumers probably don’t know is that the call center agents assisting them are most likely working from home. In fact, our recent research report, Customer Experience Management (CXM) State of the Market Report 2021, found that the percentage of CXM FTEs working at home grew from less than 10 percent in 2019 to as much as 80 percent during the health crisis. While we expect that there will be some movement back towards the brick and mortar model in the coming months and years, many service providers and in-house contact centers will continue to utilize Work at Home Agents (WAHA) as a key component of their service delivery strategy.

Two WAHA models are currently in use. One is employee-based (E-WAHA), wherein the agents are on the service provider’s or company’s payroll. The other is contract-based (C-WAHA), wherein contractors are leveraged and only paid for the time they work for the organization.

In recent years, GigCX has emerged as an alternate approach to CXM staffing and is being utilized by the likes of organizations such as eBay and Microsoft. GigCX includes the use of freelance or self-employed workers to handle specific interaction types, leveraging an AI-powered technology platform. They are recruited for their existing knowledge and passion for the product and service.

Initially, GigCX was utilized for very simple work; however, those interactions are increasingly being eliminated or automated. Now, growing use of this model is for more complex query types that require a level of brand affinity and awareness, which can be a differentiator many GigCX providers are publicizing.

GigCX, which is often seen as another strain of the WAHA model, should not be confused with WAHA, as there are some fundamental differences in how the models operate.

When considering which approach is best to meet a set of business requirements, organizations should understand the following differences in the two models:

GigCX

While we have seen both WAHA and GigCX being effective models for handling customer interactions, there are some stark differences in their operation. Any company considering using either model should assess the positives and negatives of the approaches and factor them into their operating model design. Both models are highly effective when utilized appropriately to handle the right interaction types, especially if all the limitations and dependencies are considered early in the design process.

For more information, please feel free to contact me at [email protected].

 

The Future is Calling: Contact Centers in Crisis | Webinar

Everest Group’s Sharang Sharma will share his insights on the future of contact centers on a webinar hosted by Amelia, an IPSoft company.

The global pandemic reminded us about the need to implement AI and automation technologies in contact centers to augment and scale human call center agents. It is anticipated that contact centers will never retreat to a pre-pandemic state, since consumer and business interactions have been irrevocably transformed to adjust to COVID-era buying and spending habits.

The panel of speakers will discuss the AI technologies that must be in place to optimize call center operations hinged on a hybrid workforce of digital and human agents. They will also discuss strategies to elevate customer experiences.

When

Wednesday, January 27, 9 am PST, 9 am CST, 10 am EST, 4 pm BST, 8:30 pm IST

Where

Live, virtual event

Presenters

Sharang Sharma
Practice Director
Everest Group

Eric Fradet
VP – Global Practice Head, Cloud and Infrastructure Services
Capgemini

Jonathan Crane
Chief Commercial Officer
Amelia, an IPsoft Company

 

CCAP: Leading with CX in a Digital World — July 25-26 | Event

Everest Group is once again the featured Knowledge Partner of the 2018 Contact Islands conference, “Leading with CX in a Digital World,” presented by the Contact Center Association of the Philippines (CCAP).

Managing Partner Eric Simonson and Research Partner H. Karthik will be key speakers during the event.

Eric will lead a session titled, “The Empowered Customer in the Age of Digital Care”
Session summary: Industries across the globe are facing profound paradigm shifts driven by new business models, supported by innovative, disruptive innovations. Amidst the changing business landscape, the focus on customers has become even more critical than ever before. This session aims to build a better understanding of the “new-age” customer and their expectations, focusing on both existing customer segments as well as millennials. The session re-inforces the importance of staying focused on customers while in the midst of adopting new models and undergoing transformation.

Karthik will moderate a session titled, “Gearing Up for the Hybrid Workforce: Humans + Machines”
Session summary: Next gen technologies such as AI, automation, and advanced analytics is changing the way companies operates. As humans and machines work more closely and collaborate, processes can become more fluid and adaptive and help organizations become more innovative and profitable. This session brings in the views of the leading industry voices on how they are getting ready for this shift and the kind of the steps they are taking, including the changes coming to the overall CX approach. Further, it explores how the collaborative Human + Machine service delivery model will enhance outcomes and result in more impact than ever before.

When

July 25-26, 2018

Where

Shangri-La’s Mactan Resort and Spa
Cebu, Philippines

Speakers

Eric Simonson, Managing Partner, Everest Group
H. Karthik, Partner, Research, Everest Group

Learn more

How to Operationalize AI in Contact Centers | Sherpas in Blue Shirts

All types of artificial intelligence (AI) technology – from machine learning to natural language processing to cognitive computing – are being leveraged by enterprises to drive better customer experiences and process efficiency. Based on our market research, more than one-third of enterprises have prioritized adoption of AI-powered customer experience management (CXM) solutions in the next two to three years.

Contact Centers Looking for Value in AI Face Numerous Issues

  • Lack of stakeholder buy-in: Implementation of new technologies can be a barrier for firms that have made substantial investments into existing technologies and agent skill sets
  • Workforce resistance: Agents may be afraid that their jobs will be at risk, which in turn discourages use of AI technologies
  • Poor data management: Most data currently resides in siloes, which makes it very difficult for firms to leverage it to train AI systems, and results in suboptimal returns.

Despite these challenges, AI can be a key contributor to upping organizations’ competitive capabilities in the contact center space.

Three AI Benefits in Contact Centers

  • Enhanced customer experience: AI can help steer conversations in the right direction through real-time sentiment analysis, and deliver personalized recommendations. Consider, for example, a situation wherein AI informs the contact center agent that a telecom customer, who has called for billing clarification, can save money by opting for an international roaming pack as he/she travels abroad frequently.
  • Enable highly skilled talent: AI can be leveraged to monitor agent behavior and recommend training to enhance individual agent productivity. It can also ensure process compliance through regular prompts when agents are interacting with customers.
  • Drive process efficiency: AI-based bots deployed in the back-office can tap into the large volumes of data available for analysis to anticipate customer needs and smart route the request to the best fit agent.

But, to derive real, tangible, sustainable benefits from AI, we recommend enterprises carefully address the following considerations when attempting to operationalize their AI deployments.

Key considerations to operationalize AI in contact centers

There’s no question that AI is a key enabler in driving personalized, targeted customer service. But how enterprises embrace it will mean the difference between also-ran and game-changer status.

To hear more about how some of the leading brands are strengthening their customer experience delivery, the role of next-gen technologies, and how the Philippines’ contact center industry is matching the pace of the global industry-wide disruption, we invite you to join us at the Contact Center Association of the Philippines’ annual Contact Islands conference on July 25 and 26.

Everest Group is the knowledge partner for this annual event, and two of our executives – Eric Simonson and Karthik H – will be moderating plenary sessions.

Omnichannel CX: Conquering the Challenges | Sherpas in Blue Shirts

Customers have stopped thinking about channels. It’s the experience that matters to them now – regardless of the channel they choose at any point of time. Thus, it’s no surprise that 73 percent of buyers responding to Everest Group’s 2016/17 Contact Center Outsourcing (CCO) surveys and interviews rated omnichannel as their top priority for adoption, and that 23 percent of buyers want to integrate the face-to-face customer touchpoints with their contact centers.

Omnichannel is a Priority for Adoption among CCO Buyers

CCO omnichannel CX adoption

Regardless of this intention, very few enterprises have achieved delivering a true omnichannel experience or built competitive advantage through exceptional CX.

Six Challenges Enterprises are Facing in their Transition to Omnichannel CX

Challenge 1: Lack of strategic leadership support: Most omnichannel transition efforts lack direct involvement from senior leadership to prioritize investments, communicate urgency for transition, and mitigate any implementation roadblocks. This contributes to misplaced priorities and execution inefficiencies.

Solution: An internal transition team consisting of experienced senior leadership can be set up to manage and drive the organization-wide change towards omnichannel.

Challenge 2: Inadequate focus on human capital challenges: Omni-channel investment decisions are primarily focused on technologies and solutions. But even with sophisticated tools and technologies in place, lack of investment in human capital makes it difficult to practically achieve the desired outcomes.

Solution: Organizations need to place equal importance on investments in human capital and begin their omnichannel transition efforts by assessing the talent requirements to manage omnichannel CX.

Challenge 3: Organizational skills gap for omnichannel: IT teams often lack the necessary skills to support the integration of tools, channels, and databases. Contact center managers also require upskilling on sophisticated technologies, systems, and processes to effectively manage omnichannel contact centers. Agents, usually trained in supporting individual channels, have limited knowledge to work across multiple channels.

Solution: Enterprises should conduct a gap analysis to identify training requirements for the existing talent at all levels of the organization, with the necessary skills for omni-channel and hire for new profiles. They should also revise employee performance metrics and align the incentives with common omnichannel KPIs

Challenge 4: Historically siloed functions and channels: Lack of integrated front-office functions such as sales, marketing, and customer service with back-office functions such as business intelligence, reporting, procurement, inventory management, etc., makes it impossible to create a unified view about customers.

Solution: Back-to-front office integration is crucial for a great end-to-end customer journey. The first step to achieving this is through customer journey mapping for all end-to-end processes to identify changing behaviors, capture unmet expectations, optimize processes, and encourage cross-functional collaboration.

Challenge 5: Lack of clarity on requirements for data integration from all channels: Enterprises are not clear about the business and operational needs to support data integration across all channels. Management of disparate CRM, voice and other technology systems also hinder integration.

Solution: Enterprises need to assess the implications of data standardization and integration across channels and identify an appropriate mix of tools to achieve integration of disparate datasets and applications.

Challenge 6: Incompatible legacy systems: Most legacy systems in enterprises, especially CRM systems and voice technologies, are incompatible with omnichannel platforms and solutions. This leads to inconsistency in capturing and transferring data to achieve a unified view of customers in a single platform.

Solution: Enterprises should adopt non-invasive omnichannel platforms and solutions that can seamlessly communicate with their legacy systems.

To learn more, check out Everest Group’s two-part study on omnichannel customer experience: “From Multi-Channel to Omni-Channel Customer Experience,” and “Delivering Omni-Channel Customer Experience.” Both include checklists to help enterprises successfully plan and execute their transition to omnichannel. And, please feel free to share your omnichannel experiences with us: Katrina Menzigian ([email protected]) and Jayapriya K ([email protected].)

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